| NSF Org: |
CCF Division of Computing and Communication Foundations |
| Recipient: |
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| Initial Amendment Date: | September 10, 2018 |
| Latest Amendment Date: | September 27, 2023 |
| Award Number: | 1839356 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Stacey Levine
slevine@nsf.gov (703)292-2948 CCF Division of Computing and Communication Foundations CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | October 1, 2018 |
| End Date: | September 30, 2024 (Estimated) |
| Total Intended Award Amount: | $199,983.00 |
| Total Awarded Amount to Date: | $199,983.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
1960 KENNY RD COLUMBUS OH US 43210-1016 (614)688-8735 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
OH US 43210-1101 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
TRIPODS Transdisciplinary Rese, OFFICE OF MULTIDISCIPLINARY AC, IntgStrat Undst Neurl&Cogn Sys |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
This project develops an educational program for undergraduate students, introducing them to methods at the forefront of modern mathematical and statistical data analysis through application to problems in neuroscience. The program consists of a one-semester interactive online course followed by an in-person research experience held at the Mathematical Bioscience Institute in Columbus, OH. Faculty from Ohio State University (OSU) and Pennsylvania State University (PSU) will lecture in the online course; participating student cohorts will reside at OSU, PSU, and a diverse collection of six additional US institutions - including two liberal arts colleges, two universities in Puerto Rico, an historically black university (HBCU), and a regional university with a primarily commuter student body. The project will introduce a modern area of research -- topological and geometric data analysis, to undergraduate students with different backgrounds and educational experiences, better preparing these students for graduate education and/or entry into the workforce. A flexible and accessible undergraduate curriculum in topological and geometric methods for the analysis of neuroscience data will be developed and made broadly available. A diverse community of educators will be trained to facilitate the delivery of the curriculum at their home institution, and their own research opportunities will be enhanced; an important outcome of the project is the engagement of experimental and mathematical neuroscientists in the emerging field of topological and geometric data analysis.
In this project, researchers in topological and geometric data analysis at Ohio State University (OSU) will collaborate with an experimental neuroscientist, director of the Speech, Language, and Music Lab (SLAM Lab) at OSU to develop scientific methods, curricular materials and educational projects. Research in the SLAM lab involves the use of structural and functional MRI data to identify anatomical structures and networks underlying varied abilities in speech processing, as well as the nature of brain plasticity. A flexible and accessible undergraduate curriculum in topological and geometric methods for the analysis of neuroscience data will be developed and made broadly available. An interactive online course, using the broadband facilities of the Mathematical Biosciences Institute (MBI) will be given to undergraduates at eight institutions with participation by local faculty. A following workshop at the MBI will bring together the OSU researchers, the remote faculty and the undergraduates to work on research projects. This project provides the opportunity for two cohorts of undergraduates from eight colleges and universities to participate in a unique education/research experience and for the development of a novel curriculum in topological and geometric methods for neuroscience applications. In addition, it will allow faculty from participating institutions to learn the principles of topological and geometric data analysis, providing the opportunity to broaden their research programs to include this modern area of data science.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The overarching objectives of this project were to (i) develop a flexible and accessible undergraduate curriculum in topological and geometric methods for the analysis of neuroscience data, (ii) create a diverse community of educators trained to facilitate the delivery of the curriculum
at their home institutions, (iii) introduce a modern area of research to undergraduate students with different backgrounds and educational experiences and to prepare these students for graduate education or entry into the workforce, and (iv) engage experimental and mathematical neuroscientists in the emerging field of topological and geometric data analysis. To this end, we began our efforts with a 3.5 day curriculum workshop facilitated by a professional course design consultant. The workshop participants included faculty leaders from satellite institutions. The developed course was offered synchronously online during Spring 2020. Students for the course were recruited by faculty leaders at satellite institutions as well as Ohio State. Faculty at participating institutions attended lectures and supplemented the material with their own activities and readings. At the conclusion of the course, we offered a virtual 3.5 day research experience to participating faculty and students. Unfortunately, due to disruptions caused by the COVID-19 pandemic, we were unable to offer the course in this form after the Spring 2020 semester. Instead, with the help of a postdoctoral scholar and a graduate student at Ohio State, we developed a fully asynchronous course that is now available to the public via the course webpage https://tda-and-neuro.github.io. The webpage includes a list of pre-requisites, required software, lectures with associated videos, and a description of a culminating course project. The course topics are as follows: (1) Introduction, (2) Topology, (3) Simplicial complexes, (4) Homology, (5) Persistent homology, (6) Preprocessing data, (7) Theory of persistent homology, (8) Extensions of persistent homology, (9) Visualization, (10) Neuroscience background, (11) Geometric structure of the brain, and (12) Memory.
Last Modified: 01/28/2025
Modified by: Sebastian A Kurtek
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